code: def small_abc_image_recognition():
      """!
      @brief Trains network using letters 'A', 'B', 'C', and recognize each of them with and without noise.
  
      """
      images = []
      images += IMAGE_SYMBOL_SAMPLES.LIST_IMAGES_SYMBOL_A
      images += IMAGE_SYMBOL_SAMPLES.LIST_IMAGES_SYMBOL_B
      images += IMAGE_SYMBOL_SAMPLES.LIST_IMAGES_SYMBOL_C
  
      template_recognition_image(images, 250, 25)
  
file_path: pyclustering/pyclustering/nnet/examples/syncpr_examples.py
imports: from pyclustering.samples.definitions import IMAGE_SYMBOL_SAMPLES
  from pyclustering.utils import read_image, rgb2gray
  from pyclustering.nnet import solve_type
  from pyclustering.nnet.syncpr import syncpr, syncpr_visualizer
  import random
  import math
label_desc: Use image node_id 3 for calling a global function with example usage: small_abc_image_recognition() without return types